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/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_conv_partial_fast_q15.c
* Description: Fast Q15 Partial convolution
*
* $Date: 18. March 2019
* $Revision: V1.6.0
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2019 ARM Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "arm_math.h"
/**
@ingroup groupFilters
*/
/**
@addtogroup PartialConv
@{
*/
/**
@brief Partial convolution of Q15 sequences (fast version).
@param[in] pSrcA points to the first input sequence
@param[in] srcALen length of the first input sequence
@param[in] pSrcB points to the second input sequence
@param[in] srcBLen length of the second input sequence
@param[out] pDst points to the location where the output result is written
@param[in] firstIndex is the first output sample to start with
@param[in] numPoints is the number of output points to be computed
@return execution status
- \ref ARM_MATH_SUCCESS : Operation successful
- \ref ARM_MATH_ARGUMENT_ERROR : requested subset is not in the range [0 srcALen+srcBLen-2]
@remark
Refer to \ref arm_conv_partial_q15() for a slower implementation of this function which uses a 64-bit accumulator to avoid wrap around distortion.
*/
arm_status arm_conv_partial_fast_q15(
const q15_t * pSrcA,
uint32_t srcALen,
const q15_t * pSrcB,
uint32_t srcBLen,
q15_t * pDst,
uint32_t firstIndex,
uint32_t numPoints)
{
const q15_t *pIn1; /* InputA pointer */
const q15_t *pIn2; /* InputB pointer */
q15_t *pOut = pDst; /* Output pointer */
q31_t sum, acc0, acc1, acc2, acc3; /* Accumulator */
const q15_t *px; /* Intermediate inputA pointer */
const q15_t *py; /* Intermediate inputB pointer */
const q15_t *pSrc1, *pSrc2; /* Intermediate pointers */
q31_t x0, x1, x2, x3, c0; /* Temporary input variables */
uint32_t j, k, count, blkCnt, check;
int32_t blockSize1, blockSize2, blockSize3; /* Loop counters */
arm_status status; /* Status of Partial convolution */
/* Check for range of output samples to be calculated */
if ((firstIndex + numPoints) > ((srcALen + (srcBLen - 1U))))
{
/* Set status as ARM_MATH_ARGUMENT_ERROR */
status = ARM_MATH_ARGUMENT_ERROR;
}
else
{
/* The algorithm implementation is based on the lengths of the inputs. */
/* srcB is always made to slide across srcA. */
/* So srcBLen is always considered as shorter or equal to srcALen */
if (srcALen >= srcBLen)
{
/* Initialization of inputA pointer */
pIn1 = pSrcA;
/* Initialization of inputB pointer */
pIn2 = pSrcB;
}
else
{
/* Initialization of inputA pointer */
pIn1 = pSrcB;
/* Initialization of inputB pointer */
pIn2 = pSrcA;
/* srcBLen is always considered as shorter or equal to srcALen */
j = srcBLen;
srcBLen = srcALen;
srcALen = j;
}
/* Conditions to check which loopCounter holds
* the first and last indices of the output samples to be calculated. */
check = firstIndex + numPoints;
blockSize3 = ((int32_t)check > (int32_t)srcALen) ? (int32_t)check - (int32_t)srcALen : 0;
blockSize3 = ((int32_t)firstIndex > (int32_t)srcALen - 1) ? blockSize3 - (int32_t)firstIndex + (int32_t)srcALen : blockSize3;
blockSize1 = ((int32_t) srcBLen - 1) - (int32_t) firstIndex;
blockSize1 = (blockSize1 > 0) ? ((check > (srcBLen - 1U)) ? blockSize1 : (int32_t) numPoints) : 0;
blockSize2 = (int32_t) check - ((blockSize3 + blockSize1) + (int32_t) firstIndex);
blockSize2 = (blockSize2 > 0) ? blockSize2 : 0;
/* conv(x,y) at n = x[n] * y[0] + x[n-1] * y[1] + x[n-2] * y[2] + ...+ x[n-N+1] * y[N -1] */
/* The function is internally
* divided into three stages according to the number of multiplications that has to be
* taken place between inputA samples and inputB samples. In the first stage of the
* algorithm, the multiplications increase by one for every iteration.
* In the second stage of the algorithm, srcBLen number of multiplications are done.
* In the third stage of the algorithm, the multiplications decrease by one
* for every iteration. */
/* Set the output pointer to point to the firstIndex
* of the output sample to be calculated. */
pOut = pDst + firstIndex;
/* --------------------------
* Initializations of stage1
* -------------------------*/
/* sum = x[0] * y[0]
* sum = x[0] * y[1] + x[1] * y[0]
* ....
* sum = x[0] * y[srcBlen - 1] + x[1] * y[srcBlen - 2] +...+ x[srcBLen - 1] * y[0]
*/
/* In this stage the MAC operations are increased by 1 for every iteration.
The count variable holds the number of MAC operations performed.
Since the partial convolution starts from firstIndex
Number of Macs to be performed is firstIndex + 1 */
count = 1U + firstIndex;
/* Working pointer of inputA */
px = pIn1;
/* Working pointer of inputB */
pSrc2 = pIn2 + firstIndex;
py = pSrc2;
/* ------------------------
* Stage1 process
* ----------------------*/
/* For loop unrolling by 4, this stage is divided into two. */
/* First part of this stage computes the MAC operations less than 4 */
/* Second part of this stage computes the MAC operations greater than or equal to 4 */
/* The first part of the stage starts here */
while ((count < 4U) && (blockSize1 > 0))
{
/* Accumulator is made zero for every iteration */
sum = 0;
/* Loop over number of MAC operations between
* inputA samples and inputB samples */
k = count;
while (k > 0U)
{
/* Perform the multiply-accumulates */
sum = __SMLAD(*px++, *py--, sum);
/* Decrement loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = (q15_t) (sum >> 15);
/* Update the inputA and inputB pointers for next MAC calculation */
py = ++pSrc2;
px = pIn1;
/* Increment MAC count */
count++;
/* Decrement loop counter */
blockSize1--;
}
/* The second part of the stage starts here */
/* The internal loop, over count, is unrolled by 4 */
/* To, read the last two inputB samples using SIMD:
* y[srcBLen] and y[srcBLen-1] coefficients, py is decremented by 1 */
py = py - 1;
while (blockSize1 > 0)
{
/* Accumulator is made zero for every iteration */
sum = 0;
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = count >> 2U;
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
a second loop below computes MACs for the remaining 1 to 3 samples. */
while (k > 0U)
{
/* Perform the multiply-accumulate */
/* x[0], x[1] are multiplied with y[srcBLen - 1], y[srcBLen - 2] respectively */
sum = __SMLADX(read_q15x2_ia ((q15_t **) &px), read_q15x2_da ((q15_t **) &py), sum);
/* x[2], x[3] are multiplied with y[srcBLen - 3], y[srcBLen - 4] respectively */
sum = __SMLADX(read_q15x2_ia ((q15_t **) &px), read_q15x2_da ((q15_t **) &py), sum);
/* Decrement loop counter */
k--;
}
/* For the next MAC operations, the pointer py is used without SIMD
So, py is incremented by 1 */
py = py + 1U;
/* If the count is not a multiple of 4, compute any remaining MACs here.
No loop unrolling is used. */
k = count % 0x4U;
while (k > 0U)
{
/* Perform the multiply-accumulates */
sum = __SMLAD(*px++, *py--, sum);
/* Decrement loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = (q15_t) (sum >> 15);
/* Update the inputA and inputB pointers for next MAC calculation */
py = ++pSrc2 - 1U;
px = pIn1;
/* Increment MAC count */
count++;
/* Decrement loop counter */
blockSize1--;
}
/* --------------------------
* Initializations of stage2
* ------------------------*/
/* sum = x[0] * y[srcBLen-1] + x[1] * y[srcBLen-2] +...+ x[srcBLen-1] * y[0]
* sum = x[1] * y[srcBLen-1] + x[2] * y[srcBLen-2] +...+ x[srcBLen] * y[0]
* ....
* sum = x[srcALen-srcBLen-2] * y[srcBLen-1] + x[srcALen] * y[srcBLen-2] +...+ x[srcALen-1] * y[0]
*/
/* Working pointer of inputA */
if ((int32_t)firstIndex - (int32_t)srcBLen + 1 > 0)
{
pSrc1 = pIn1 + firstIndex - srcBLen + 1;
}
else
{
pSrc1 = pIn1;
}
px = pSrc1;
/* Working pointer of inputB */
pSrc2 = pIn2 + (srcBLen - 1U);
py = pSrc2;
/* count is the index by which the pointer pIn1 to be incremented */
count = 0U;
/* -------------------
* Stage2 process
* ------------------*/
/* Stage2 depends on srcBLen as in this stage srcBLen number of MACS are performed.
* So, to loop unroll over blockSize2,
* srcBLen should be greater than or equal to 4 */
if (srcBLen >= 4U)
{
/* Loop unrolling: Compute 4 outputs at a time */
blkCnt = ((uint32_t) blockSize2 >> 2U);
while (blkCnt > 0U)
{
py = py - 1U;
/* Set all accumulators to zero */
acc0 = 0;
acc1 = 0;
acc2 = 0;
acc3 = 0;
/* read x[0], x[1] samples */
x0 = read_q15x2 ((q15_t *) px);
/* read x[1], x[2] samples */
x1 = read_q15x2 ((q15_t *) px + 1);
px += 2U;
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = srcBLen >> 2U;
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
** a second loop below computes MACs for the remaining 1 to 3 samples. */
do
{
/* Read the last two inputB samples using SIMD:
* y[srcBLen - 1] and y[srcBLen - 2] */
c0 = read_q15x2_da ((q15_t **) &py);
/* acc0 += x[0] * y[srcBLen - 1] + x[1] * y[srcBLen - 2] */
acc0 = __SMLADX(x0, c0, acc0);
/* acc1 += x[1] * y[srcBLen - 1] + x[2] * y[srcBLen - 2] */
acc1 = __SMLADX(x1, c0, acc1);
/* Read x[2], x[3] */
x2 = read_q15x2 ((q15_t *) px);
/* Read x[3], x[4] */
x3 = read_q15x2 ((q15_t *) px + 1);
/* acc2 += x[2] * y[srcBLen - 1] + x[3] * y[srcBLen - 2] */
acc2 = __SMLADX(x2, c0, acc2);
/* acc3 += x[3] * y[srcBLen - 1] + x[4] * y[srcBLen - 2] */
acc3 = __SMLADX(x3, c0, acc3);
/* Read y[srcBLen - 3] and y[srcBLen - 4] */
c0 = read_q15x2_da ((q15_t **) &py);
/* acc0 += x[2] * y[srcBLen - 3] + x[3] * y[srcBLen - 4] */
acc0 = __SMLADX(x2, c0, acc0);
/* acc1 += x[3] * y[srcBLen - 3] + x[4] * y[srcBLen - 4] */
acc1 = __SMLADX(x3, c0, acc1);
/* Read x[4], x[5] */
x0 = read_q15x2 ((q15_t *) px + 2);
/* Read x[5], x[6] */
x1 = read_q15x2 ((q15_t *) px + 3);
px += 4U;
/* acc2 += x[4] * y[srcBLen - 3] + x[5] * y[srcBLen - 4] */
acc2 = __SMLADX(x0, c0, acc2);
/* acc3 += x[5] * y[srcBLen - 3] + x[6] * y[srcBLen - 4] */
acc3 = __SMLADX(x1, c0, acc3);
} while (--k);
/* For the next MAC operations, SIMD is not used
So, the 16 bit pointer if inputB, py is updated */
/* If the srcBLen is not a multiple of 4, compute any remaining MACs here.
No loop unrolling is used. */
k = srcBLen % 0x4U;
if (k == 1U)
{
/* Read y[srcBLen - 5] */
c0 = *(py + 1);
#ifdef ARM_MATH_BIG_ENDIAN
c0 = c0 << 16U;
#else
c0 = c0 & 0x0000FFFF;
#endif /* #ifdef ARM_MATH_BIG_ENDIAN */
/* Read x[7] */
x3 = read_q15x2 ((q15_t *) px);
px++;
/* Perform the multiply-accumulate */
acc0 = __SMLAD (x0, c0, acc0);
acc1 = __SMLAD (x1, c0, acc1);
acc2 = __SMLADX(x1, c0, acc2);
acc3 = __SMLADX(x3, c0, acc3);
}
if (k == 2U)
{
/* Read y[srcBLen - 5], y[srcBLen - 6] */
c0 = read_q15x2 ((q15_t *) py);
/* Read x[7], x[8] */
x3 = read_q15x2 ((q15_t *) px);
/* Read x[9] */
x2 = read_q15x2 ((q15_t *) px + 1);
px += 2U;
/* Perform the multiply-accumulate */
acc0 = __SMLADX(x0, c0, acc0);
acc1 = __SMLADX(x1, c0, acc1);
acc2 = __SMLADX(x3, c0, acc2);
acc3 = __SMLADX(x2, c0, acc3);
}
if (k == 3U)
{
/* Read y[srcBLen - 5], y[srcBLen - 6] */
c0 = read_q15x2 ((q15_t *) py);
/* Read x[7], x[8] */
x3 = read_q15x2 ((q15_t *) px);
/* Read x[9] */
x2 = read_q15x2 ((q15_t *) px + 1);
/* Perform the multiply-accumulate */
acc0 = __SMLADX(x0, c0, acc0);
acc1 = __SMLADX(x1, c0, acc1);
acc2 = __SMLADX(x3, c0, acc2);
acc3 = __SMLADX(x2, c0, acc3);
c0 = *(py-1);
#ifdef ARM_MATH_BIG_ENDIAN
c0 = c0 << 16U;
#else
c0 = c0 & 0x0000FFFF;
#endif /* #ifdef ARM_MATH_BIG_ENDIAN */
/* Read x[10] */
x3 = read_q15x2 ((q15_t *) px + 2);
px += 3U;
/* Perform the multiply-accumulates */
acc0 = __SMLADX(x1, c0, acc0);
acc1 = __SMLAD (x2, c0, acc1);
acc2 = __SMLADX(x2, c0, acc2);
acc3 = __SMLADX(x3, c0, acc3);
}
/* Store the results in the accumulators in the destination buffer. */
#ifndef ARM_MATH_BIG_ENDIAN
write_q15x2_ia (&pOut, __PKHBT(acc0 >> 15, acc1 >> 15, 16));
write_q15x2_ia (&pOut, __PKHBT(acc2 >> 15, acc3 >> 15, 16));
#else
write_q15x2_ia (&pOut, __PKHBT(acc1 >> 15, acc0 >> 15, 16));
write_q15x2_ia (&pOut, __PKHBT(acc3 >> 15, acc2 >> 15, 16));
#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
/* Increment the pointer pIn1 index, count by 4 */
count += 4U;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pSrc1 + count;
py = pSrc2;
/* Decrement the loop counter */
blkCnt--;
}
/* If the blockSize2 is not a multiple of 4, compute any remaining output samples here.
No loop unrolling is used. */
blkCnt = (uint32_t) blockSize2 % 0x4U;
while (blkCnt > 0U)
{
/* Accumulator is made zero for every iteration */
sum = 0;
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = srcBLen >> 2U;
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
a second loop below computes MACs for the remaining 1 to 3 samples. */
while (k > 0U)
{
/* Perform the multiply-accumulates */
sum += ((q31_t) *px++ * *py--);
sum += ((q31_t) *px++ * *py--);
sum += ((q31_t) *px++ * *py--);
sum += ((q31_t) *px++ * *py--);
/* Decrement loop counter */
k--;
}
/* If the srcBLen is not a multiple of 4, compute any remaining MACs here.
** No loop unrolling is used. */
k = srcBLen % 0x4U;
while (k > 0U)
{
/* Perform the multiply-accumulates */
sum += ((q31_t) *px++ * *py--);
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = (q15_t) (sum >> 15);
/* Increment the pointer pIn1 index, count by 1 */
count++;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pSrc1 + count;
py = pSrc2;
/* Decrement loop counter */
blkCnt--;
}
}
else
{
/* If the srcBLen is not a multiple of 4,
* the blockSize2 loop cannot be unrolled by 4 */
blkCnt = (uint32_t) blockSize2;
while (blkCnt > 0U)
{
/* Accumulator is made zero for every iteration */
sum = 0;
/* srcBLen number of MACS should be performed */
k = srcBLen;
while (k > 0U)
{
/* Perform the multiply-accumulate */
sum += ((q31_t) *px++ * *py--);
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = (q15_t) (sum >> 15);
/* Increment the MAC count */
count++;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pSrc1 + count;
py = pSrc2;
/* Decrement the loop counter */
blkCnt--;
}
}
/* --------------------------
* Initializations of stage3
* -------------------------*/
/* sum += x[srcALen-srcBLen+1] * y[srcBLen-1] + x[srcALen-srcBLen+2] * y[srcBLen-2] +...+ x[srcALen-1] * y[1]
* sum += x[srcALen-srcBLen+2] * y[srcBLen-1] + x[srcALen-srcBLen+3] * y[srcBLen-2] +...+ x[srcALen-1] * y[2]
* ....
* sum += x[srcALen-2] * y[srcBLen-1] + x[srcALen-1] * y[srcBLen-2]
* sum += x[srcALen-1] * y[srcBLen-1]
*/
/* In this stage the MAC operations are decreased by 1 for every iteration.
The count variable holds the number of MAC operations performed */
count = srcBLen - 1U;
/* Working pointer of inputA */
pSrc1 = (pIn1 + srcALen) - (srcBLen - 1U);
px = pSrc1;
/* Working pointer of inputB */
pSrc2 = pIn2 + (srcBLen - 1U);
pIn2 = pSrc2 - 1U;
py = pIn2;
/* -------------------
* Stage3 process
* ------------------*/
/* For loop unrolling by 4, this stage is divided into two. */
/* First part of this stage computes the MAC operations greater than 4 */
/* Second part of this stage computes the MAC operations less than or equal to 4 */
/* The first part of the stage starts here */
j = count >> 2U;
while ((j > 0U) && (blockSize3 > 0))
{
/* Accumulator is made zero for every iteration */
sum = 0;
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = count >> 2U;
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
** a second loop below computes MACs for the remaining 1 to 3 samples. */
while (k > 0U)
{
/* x[srcALen - srcBLen + 1], x[srcALen - srcBLen + 2] are multiplied
* with y[srcBLen - 1], y[srcBLen - 2] respectively */
sum = __SMLADX(read_q15x2_ia ((q15_t **) &px), read_q15x2_da ((q15_t **) &py), sum);
/* x[srcALen - srcBLen + 3], x[srcALen - srcBLen + 4] are multiplied
* with y[srcBLen - 3], y[srcBLen - 4] respectively */
sum = __SMLADX(read_q15x2_ia ((q15_t **) &px), read_q15x2_da ((q15_t **) &py), sum);
/* Decrement loop counter */
k--;
}
/* For the next MAC operations, the pointer py is used without SIMD
So, py is incremented by 1 */
py = py + 1U;
/* If the count is not a multiple of 4, compute any remaining MACs here.
No loop unrolling is used. */
k = count % 0x4U;
while (k > 0U)
{
/* sum += x[srcALen - srcBLen + 5] * y[srcBLen - 5] */
sum = __SMLAD(*px++, *py--, sum);
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = (q15_t) (sum >> 15);
/* Update the inputA and inputB pointers for next MAC calculation */
px = ++pSrc1;
py = pIn2;
/* Decrement the MAC count */
count--;
/* Decrement the loop counter */
blockSize3--;
j--;
}
/* The second part of the stage starts here */
/* SIMD is not used for the next MAC operations,
* so pointer py is updated to read only one sample at a time */
py = py + 1U;
while (blockSize3 > 0)
{
/* Accumulator is made zero for every iteration */
sum = 0;
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = count;
while (k > 0U)
{
/* Perform the multiply-accumulates */
/* sum += x[srcALen-1] * y[srcBLen-1] */
sum = __SMLAD(*px++, *py--, sum);
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = (q15_t) (sum >> 15);
/* Update the inputA and inputB pointers for next MAC calculation */
px = ++pSrc1;
py = pSrc2;
/* Decrement the MAC count */
count--;
/* Decrement the loop counter */
blockSize3--;
}
/* Set status as ARM_MATH_SUCCESS */
status = ARM_MATH_SUCCESS;
}
/* Return to application */
return (status);
}
/**
@} end of PartialConv group
*/